1. Field of the Invention
The present invention relates to an apparatus or method for performing color processing using a table whose inputs are a fundamental stimulus value and a spectral support coefficient.
2. Description of the Related Art
Heretofore, the colors of colorants generating an output image of a color recording apparatus have been generally the three colors of cyan (C), magenta (M), and yellow (Y), which are the three primary colors serving as a subtractive color mixture, or the four colors, which black (K) is added thereto. In this case, the three color components of red (R), green (G), and blue (B) of input image data have been converted into the three colors of C, M, and Y, or the four colors including K, thereby generating an image using the colorant of each color. Also, in recent years, color reproduction apparatuses have been put on the market wherein in addition to the four fundamental colorants of C, M, Y, and K, the other colorants other than the three primary colors serving as a subtractive color mixture, i.e., the three colors of RGB serving as additional colors other than the fundamental colorants, such as red, green, blue, orange, and violet are added as colorants. Such a color reproduction apparatus can provide color reproduction that cannot be achieved with image reproduction using existing three colors or four colors.
Also, the demand for high image quality is increasing along with the rapid spread of color reproduction apparatuses in recent years, and it has been proposed to employ the spectral information of a visible wavelength region serving as input information to be given to color reproduction apparatuses. A color management system incorporating such spectral information (hereafter, referred to as spectral CMS) determines an output color such that the spectral error as to spectral information to be input becomes the minimum. Thus, in terms of the color appearance, an output image can be generated to match an input regardless of viewing conditions such as illuminant under viewing condition and so forth, i.e., metamerism can be reduced.
However, within the spectral CMS, the number of dimensions of data to be handled markedly increases, compared with the tristimulus values represented by the existing CIELAB, CIEXYZ, and so forth. For example, when sampling spectral information in a range of 400 nm through 700 nm in increments of 10 nm, spectral data to be obtained becomes 31 dimensions. In order to construct a simpler spectral CMS, it becomes important to reduce the number of dimensions without losing spectral information, and also to perform data compression effectively.
As for a data compression method of spectral information, a method for compressing spectral information employing spectral color space called as six-dimensional LabPQR has been proposed (see M. Derhak, M. Rosen, “Spectral Colorimetry Using LabPQR—An Interim Connection Space”, Color Imaging Conference 2004, U.S.A., Imaging Science and Technology, November 2004, pp 246-250). This LabPQR includes L*a*b* values, so under a specific viewing condition on which the L*a*b* values depend, the same color reproduction as colorimetry color reproduction can be achieved. The LabPQR further includes PQR serving as spectral information, whereby metamerism can be reduced.
Also, with the above-described spectral CMS employing the LabPQR, a method for determining an output color rapidly using a color lookup table (CLUT) has been proposed (see S. Tsutsumi, M. Rosen, R. Berns, “Spectral Reproduction using LabPQR: Inverting the Fractional-Area-Coverage-to-Spectra Relationship”, International Congress of Imaging Science, U.S.A., Imaging Science and Technology, May 2006, pp 107-110).
With a method for determining an output color of a reproduction apparatus via the spectral color space LabPQR of six dimensions based on spectral information to be input, in order to implement the spectral CMS using the CLUT, it is necessary to employ the six-dimensional CLUT. Accordingly, this causes a problem wherein the memory size for recording such a CLUT increases.
Further, with S. Tsutsumi, M. Rosen, R. Berns, “Spectral Reproduction using LabPQR: Inverting the Fractional-Area-Coverage-to-Spectra Relationship”, International Congress of Imaging Science, U.S.A., Imaging Science and Technology, May 2006, pp 107-110, there is description wherein the spectral CMS employing the CLUT made up of the six-dimensional LabPQR is performed, but a method for generating the CLUT is not described at all.